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. 2010 Oct 18:9:60.
doi: 10.1186/1475-925X-9-60.

Effect of slice thickness on brain magnetic resonance image texture analysis

Sami J Savio  1 , Lara C V Harrison, Tiina Luukkaala, Tomi Heinonen, Prasun Dastidar, Seppo Soimakallio, Hannu J Eskola
Affiliations

Effect of slice thickness on brain magnetic resonance image texture analysis

Sami J Savio et al. Biomed Eng Online. .

Abstract

Background: The accuracy of texture analysis in clinical evaluation of magnetic resonance images depends considerably on imaging arrangements and various image quality parameters. In this paper, we study the effect of slice thickness on brain tissue texture analysis using a statistical approach and classification of T1-weighted images of clinically confirmed multiple sclerosis patients.

Methods: We averaged the intensities of three consecutive 1-mm slices to simulate 3-mm slices. Two hundred sixty-four texture parameters were calculated for both the original and the averaged slices. Wilcoxon's signed ranks test was used to find differences between the regions of interest representing white matter and multiple sclerosis plaques. Linear and nonlinear discriminant analyses were applied with several separate training and test sets to determine the actual classification accuracy.

Results: Only moderate differences in distributions of the texture parameter value for 1-mm and simulated 3-mm-thick slices were found. Our study also showed that white matter areas are well separable from multiple sclerosis plaques even if the slice thickness differs between training and test sets.

Conclusions: Three-millimeter-thick magnetic resonance image slices acquired with a 1.5 T clinical magnetic resonance scanner seem to be sufficient for texture analysis of multiple sclerosis plaques and white matter tissue.

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Figures

Figure 1
Figure 1
Averaging of three sequential slices. The intensities of three sequential slices at both imaging levels were averaged by Matlab to obtain simulated 3-mm slices. For each pixel in the simulated image, the corresponding pixel values of three consecutive 1-mm slices were added up and the sum divided by three, after which the result was rounded to the nearest integer.
Figure 2
Figure 2
Investigated ROIs. On the left: An original T1 MPR image of an MS patient. On the right: ROIs drawn on the image. NAWM is indicated by a grey arrow and MS plaques by white arrows. (Both regular and hand drawn ROIs on an MS plaque are shown.) Normal white matter is indicated by a grey arrowhead.
See this image and copyright information in PMC

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